Monthly Archives: May 2013

Here is a recent article about high school students manipulating their Facebook presence to fool college admissions officers. Not terribly surprising: the content is (largely) created and controlled by the target of the background searches (by admissions, prospective employers, prospective dating partners etc) so it’s easy to manipulate. We’ve been seeing this sort of manipulation since the early days of user-contributed content.
People mining user-contributed content should be giving careful thought to this. Social scientists like it when they can observe behavior, because it often reveals something more authentic than simply asking someone a question (about what they like, or what they would have done in a hypothetical situation, etc). Economists, for example, are thrilled when they get to observe “revealed preference”, which are choices people make when faced with a true resource allocation problem. It could be that I purchased A instead of B to fool an observer, but there is a cost to my doing so (I bought and paid for a product that I didn’t want), and as long as the costs are sufficiently salient, it is more likely that we are observing preferences untainted by manipulation.
There are costs to manipulating user-contributed content, like Facebook profiles, of course: some amount of time, at the least, and probably some reduced value from the service (for example, students say that during college application season they hide their “regular” Facebook profile, and create a dummy in which they talk about all of the community service they are doing, and how they love bunnies and want to solve world hunger: all fine, but they are giving up the other uses of Facebook that they normally prefer). But costs of manipulating user-contributed content often may be low, and thus we shouldn’t be surprised if there is substantial manipulation in the data, especially if the users have reason to think they are being observed in a way that will affect an outcome they care about (like college admissions).
Put another way, the way people portray themselves online is behavior and so reveals something, but it may not reveal what the data miner thinks it does.